The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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Development of a novel hybrid alphavirus-SARS-CoV-2 particle for rapid in vitro screening and quantification of neutralization antibodies, viral variants, and antiviral drugs
This article has 16 authors:Reviewed by ScreenIT
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Debiasing Covid-19 prevalence estimates
This article has 3 authors:Reviewed by ScreenIT
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Evolutionary Tracking of SARS-CoV-2 Genetic Variants Highlights an Intricate Balance of Stabilizing and Destabilizing Mutations
This article has 6 authors:Reviewed by ScreenIT
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Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19
This article has 14 authors:Reviewed by ScreenIT
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Mortality rate and estimate of fraction of undiagnosed COVID-19 cases in the US in March and April 2020
This article has 2 authors:Reviewed by ScreenIT
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Public policy and economic dynamics of COVID-19 spread: A mathematical modeling study
This article has 3 authors:Reviewed by ScreenIT
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Versatile and flexible microfluidic qPCR test for high-throughput SARS-CoV-2 and cellular response detection in nasopharyngeal swab samples
This article has 18 authors:Reviewed by ScreenIT
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Risk factors for transfer from Respiratory Intermediate Care Unit to Intensive Care Unit in COVID-19
This article has 10 authors:Reviewed by ScreenIT
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Dynamics of SARS-CoV-2 with waning immunity in the UK population
This article has 12 authors:Reviewed by ScreenIT
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Reported COVID-19 Incidence in Wisconsin High School Athletes in Fall 2020
This article has 7 authors:Reviewed by ScreenIT